Effectiveness of mobile health for exercise promotion on cardiorespiratory fitness after a cancer diagnosis: A systematic review and meta‐analysis

Abstract Background Cancer survivors are at greater risk for cardiovascular‐related mortality. Mobile health (mHealth) is an increasingly prevalent strategy for health promotion, but whether it consistently improves cardiorespiratory outcomes after a cancer diagnosis is unknown. We sought to determine the effectiveness of mHealth fitness/physical activity interventions on cardiorespiratory fitness outcomes among cancer patients and survivors. Methods Leveraging MEDLINE/PubMed, Scopus, and ClinicalTrials.gov, we identified studies through May 2023. Included studies provided a quantitative evaluation of an mHealth intervention in a primary or secondary capacity on cardiorespiratory fitness (6‐minute walk test, VO2max, 3‐minute step test, or systolic blood pressure; or any mention of cardiac measure) and were meta‐analyzed (using a random effects model) if they were a randomized controlled trial with sufficient quantitative information. Four coders were involved in applying inclusion/exclusion criteria, coding using a standardized data extraction sheet, and assessing study quality, with each study coded by at least two. Results Of 656 articles, nine (n = 392) met systematic review inclusion criteria (mean age range 19–62 years, 71.9% female, 60.9% breast cancer). Interventions included mobile apps (k = 6), smartwatches (k = 2), or a smartwatch plus a supplemental web/mobile/tablet app (k = 1); median duration of mHealth‐use was 12 weeks. Seven (n = 341) fit criteria for meta‐analysis. mHealth was associated with improved cardiorespiratory fitness (d = 0.33; 95% CI = 0.07–0.60) compared to a control group. Relationships remained after accounting for lipid‐based outcomes (d = 0.30; 95% CI = 0.03–0.56). There was no evidence for heterogeneity or publication‐bias. Conclusions mHealth exercise interventions appear to be a viable strategy for improving cardiorespiratory fitness after a cancer diagnosis.


| INTRODUCTION
Cardiovascular disease (CVD) has become an increasingly common limitation to effective cancer therapy. 1,2Over the last two decades, there has been dramatic improvement in early cancer survival.However, concurrently, CVD has become increasingly prevalent among patients initially surviving cancer, with a reported incidence of up to 38%. 1 Many cardiovascular events cause serious declines in cardiorespiratory fitness and lead to debility.Unfortunately, widely available strategies to consistently improve cardiorespiratory fitness and reduce limiting CVD are largely unavailable.
Nonetheless, the landscape of healthcare has witnessed notable transformations spurred by legislative reforms and technological advancements, particularly in the United States, over the past decade.Health information technology (HIT) applications have experienced an upsurge in utilization as a result.Among these applications, electronic health records (EHRs) have become ubiquitous, often complemented by the availability and growing popularity of mobile health (mHealth) applications (or apps).Emerging isolated studies have shown that health promotion apps, such as those that guide users through exercise regimens or encourage physical activity, may improve cardiovascular risk by improving cardiorespiratory fitness and risk factors. 3,4Given the high burden of CVD seen after a cancer diagnosis, novel mHealth strategies could present a widely available and effective means for fitness optimization.Whether app-based interventions consistently improve cardiorespiratory outcomes after a cancer diagnosis, and the magnitude of these effects, are unknown.
The purpose of this study was to conduct a systematic review and meta-analysis of existing literature pertaining to the utilization and effects of mHealth technology on cardiorespiratory fitness in cancer patients (defined as people in active treatment) and survivors (defined as people who completed active treatment).By analyzing the available data, this research aims to shed light on the efficacy of mHealth interventions in this context and provide valuable insights into the potential benefits they may offer in optimizing cardiorespiratory health for these groups.Finally, findings from our study may also inform future research agenda that may facilitate development of strategies to manage cardiorespiratory fitness among cancer patients and survivors.

| Literature search and inclusion criteria
We followed a protocol consistent with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines.Specifically, we searched the PubMed, Scopus, and Clini calTr ials.gov databases through May 1, 2023, for any articles that evaluated mHealth apps in the context of cardiorespiratory fitness among cancer patients or survivors.We did not restrict our study to a beginning date.In order to be inclusive, we also evaluated gray literature to ensure that we included all possible studies that aligned with our search strategy.Articles were identified using keywords related to mHealth, health promotion, cancer patients, survivors, and cardiorespiratory fitness (see Appendix S1 for terms).Further, we contacted authors via email to request missing data if needed.Inclusion criteria entailed: (1) Study design: randomized controlled trials (RCTs) for the meta-analysis, and RCTs and observational studies or pre-post studies without a control group (including feasibility/pilot studies) for the systematic review; (2) Participants: cancer patients and/or survivors; (3) Intervention: utilization of mobile health (mHealth) technologies for physical activity or fitness; (4) Outcome: cardiorespiratory fitness (including but not limited to the 6 Minute Walk Test, VO 2 max, and heart rate outcomes).Additionally, only empirical studies were included in our review and thus excluded articles such as government reports, white papers, commentaries, opinions, perspectives, and policy briefs.This review was not registered.

| Screening and data extraction
The keyword search identified 656 unique articles which were subjected to the process shown in Figure 1.Each article was independently reviewed by at least two reviewers with a total of four reviewers performing the initial title and abstract screening.Discrepancies were resolved through discussion and consensus.Data from included studies were extracted using a standardized data extraction form to systematically code relevant information, such as study characteristics, demographics, intervention details, outcome measures, and effect sizes.Cohen's d effect size index was used to quantify the effect size for articles in the cancer survivorship, cardio-oncology, cardiorespiratory fitness, mobile health applications meta-analysis.When a negative change indicated a positive outcome (e.g., reduction in cholesterol), the inverse of the effect size was computed to ensure consistency in the direction of effect size interpretation.If multiple relevant outcomes were reported within a study, mean composites were created to obtain a single effect size per study.If a study reported multiple post-intervention time points, data from the most proximal time point were used for the analysis.Four coders were involved in data extraction, with each study double-coded by at least two reviewers.Discrepancies were resolved by the first author who reviewed the article in question and made a final decision.

| Meta-analysis
A random-effects model was used to pool the effect sizes across studies, and studies were weighted by the reciprocal of the sampling variance using the DerSimonian and Laird method. 5The meta-analysis was conducted using the "metafor" package in R. 6 To assess publication bias, several methods were employed, including a funnel plot, the Trim and Fill method, 7 the rank correlation test, 8 Egger's test, 9 and a cumulative meta-analysis 10 to explore the impact of study size on the overall effect size estimation.To assess the robustness and reliability of the meta-analysis findings, sensitivity analyses, including influence analyses and leaveone-out analysis, were conducted.We also examined the impact of specific variables on the overall effect, including intervention duration (<12 weeks, >12 weeks), cancer type (breast cancer vs. others), and outcomes (6-minute walk test only; inclusion vs. non-inclusion of cholesterol outcomes).

| Study quality assessment
We assessed quality of the included studies using two different tools: Cochrane Collaboration's Risk of Bias Tool 11 (for RCTs) and a quality rating tool from the National Institutes of Health 12 (for observational studies and prepost studies without a control group).Quality assessment coding was done by two independent coders, and discrepancies were resolved via discussion.

| Meta-analytic results
Across the seven studies in the meta-analysis, mHealth was associated with improved cardiorespiratory outcomes (d = 0.33; 95% CI = 0.07, 0.60; see Figure 2 for forest plot).There was no evidence of heterogeneity (Q = 5.86, p = 0.44).There was no evidence of publication bias (details in Appendix S2).There was one possible outlier, Chang et al., 13 which if removed, would modify the overall effect size from d = 0.33 to d = 0.23 (Appendix S3).Upon further examination, we noted that this study differed from others in our sample in three ways that could potentially account for the differences: first, the cancer type was esophageal, whereas the other studies in the metaanalysis were breast cancer (k = 5) or multiple adolescent and young adult cancers (k = 1); second, this was an esophagectomy-based study, wherein patients had major surgery to remove the esophagus, which is unique in our sample of studies; third, the proportion of females in this study was low (9%), compared to moderate-to-high proportions of female participants (49%-100%) in the other studies in the meta-analysis.
As sensitivity analyses, we ran the meta-analysis in four other ways: adding in cholesterol outcomes from Murphy et al., 4 including only 6-minute walk test outcomes, including only breast cancer studies, and including only studies with interventions of <12 weeks.Results maintained significance when cholesterol outcomes were added to the other cardiorespiratory outcomes (d = 0.30; 95% CI = 0.03, 0.56).Results of the meta-analysis containing only the 6-minute walk test (k = 4, d = 0.27, 95% CI = −0.20,0.74), only breast cancer groups (k = 5, d = 0.20, 95% CI = −0.10,0.51), and only studies <12 weeks (k = 6, d = 0.29, 95% CI = −0.06,0.63) were not significant.Given the small number of studies, analyses were underpowered, and thus more studies should be conducted to confirm these findings.See Appendix S3 for more detail.

| DISCUSSION
In this evaluation of the efficacy of mHealth-based interventions, mHealth guided physical activity and exercise interventions were associated with increased cardiorespiratory fitness following a cancer diagnosis.These observations are of particular importance given the increasing observation of limiting cardiovascular disease after cancer treatment, and the relative paucity of available strategies to consistently improve outcomes.The observed efficacy of mHealth-based exercise in improving cardiorespiratory outcomes adds to a growing body of evidence linking isolated electronic based applications with better cardiovascular measures.In animal studies, exercise attenuates chemotherapy-induced cardiotoxicity, reflected by better ventricular performance, less subclinical injury, and fewer heart failure events.Similarly, in cancer and non-cancer patients, mHealth based-exercise strategies are linked with improved well-being.In available isolated clinical studies, mHealth-based applications improve body mass index, weight, and waist circumference from using mHealth in cancer survivors. 14Furthermore, in patients treated with systemic anticancer therapies, the use of an mHealth-based strategy for improved pulmonary rehabilitation was safe, well-accepted, and efficacious in improving functional outcomes.Yet, consistent data on the effects of mHealth-based strategies on cardiorespiratory measures among cancer patients or survivors has been largely unavailable.
To our knowledge, this systematic review and metaanalysis is the first of its kind to examine the impact of mHealth interventions on objective measures of cardiorespiratory fitness in cancer patients and survivors.Our findings suggest that mHealth interventions are effective at improving cardiorespiratory fitness in this population, with most trials showing such results in <12 weeks of mHealth use.Given the demonstrated importance of fitness 15 and the high rate of cardiovascular disease in cancer survivors, 1 these findings support continued research of mHealth interventions in this population.These findings support the preponderance of mHealth evidence in the oncology literature, with meta-analyses and systematic reviews demonstrating that mHealth tools can improve QOL 16,17 and pain and fatigue management. 18,19In addition to studies with patient-centered variables, studies examining objective measures of physical activity 20 and frailty 21 among cancer patients have demonstrated the efficacy of mHealth interventions.Our findings are similar to a prior review 14 which found improvements in body mass index, weight, and waist circumference from using mHealth in this population.Our work extends these findings by showing that cardiorespiratory outcomes such as the 6MWT, blood pressure, VO 2 max, resting heart rate, and cholesterol can also be significantly improved.
These findings outline a potential role for mHealth in improving outcomes among cancer survivors, particularly those with comorbid CVD.Given the significant incidence of CVD in cancer survivors, 1 22 therefore it is possible that the inclusion of wearable devices was a key explanation for the observed improvements in cardiopulmonary fitness.An additional mechanism could be the inclusion of telehealth coaching in several studies.
Our study has the following limitations; most notably, sample size.Despite our best attempts at identifying all possible studies, only nine studies met final inclusion criteria for a total sample size of 392 patients, with only seven studies able to be included in the meta-analysis.However, this is also a reflection of the sparse nature of literature in the emergent use of mHealth apps to manage cardiorespiratory fitness among patients with cancer.Further, due to the small sample sizes of the included studies, statistical power was limited which may potentially affect generalizability.Another limitation is the heterogeneity of populations selected, which included several types of cancer at variable stages.It is possible that mHealth interventions could have variable effects in different populations, or at certain stages of disease.More studies will be required to elucidate the effects of mHealth in the widely heterogenous cancer survivor populations.Similarly, due to the small number of studies available, we were unable to test whether certain features of mHealth (e.g., frequency of reminders, addition of coaching, etc.) were more effective than others.Future work should be done to better understand this.

| CONCLUSION
mHealth exercise interventions appear to be associated with small-to-moderate improvements in cardiorespiratory fitness for cancer patients and survivors.Considering the promise these apps may present as suggested by our findings and the sparse number of studies identified by our literature, there is a need for more research that utilizes rigorous and robust study designs.Further, future studies should also focus on improving precision of the effect size estimate, and to understand conditions under which mHealth is most impactful.

1
Study characteristics table.
Study quality for RCTs.
T A B L E 2Abbreviations: H, high risk of bias; L, low risk of bias, U, unclear risk of bias.
mHealth could represent an important adjunctive treatment modality to prevent cardiovascular complications following a cancer diagnosis by providing educational materials, facilitating individualized coaching, and improving adherence to cardiovascular exercise, as these elements were present in many successful interventions.An alternative mechanism by Study quality for pre-post studies.
T A B L E 3 which mHealth improved physical fitness was by inclusion of wearable fitness tracking technology which likely increased adherence to exercise regimens.Prior studies have shown that smartwatch-based interventions significantly increase exercise and daily step count,